Optimal Energy Management And Configuration For Stationary Super Capacitor Energy Storage System Applied In Urban Rail Transit Based On Hybrid Particle Swarm Algorithm

Urban rail transit is at a stage of rapid development in China, and it has significant advantages of large capacity, punctuality, safety, energy conservation and environmental protection compared with other transportation means. How to recycle the regenerative braking energy of vehicles and reduce the energy consumption effectively, and how to improve the voltage profile of DC network and ensure the traction/braking performance of vehicles, have become hotspots in the research of urban rail transit. The installation of stationary super capacitor energy storage system (ESS) in urban rail power supply system can recycle the vehicle braking energy and improve pantograph voltage profile for the advantages of high power density, a long cycle life and convenient management. Based on the background, this paper has a deep research on the optimization of energy management strategy and configuration for multiple super capacitor ESSs applied in substations of urban railway line.This paper analyses the principle and features of vehicles, substations and super capacitor ESSs in detail, which provide the optimization research basis for energy management strategy and configuration of super capacitor ESSs in later chapters.Because of the deficiencies of typical DC voltage double-loop control strategy, this paper proposes a dynamic threshold energy management strategy based on no-load voltage and SOC(state of charge).According to terminal voltage of super capacitors and grid-side voltage of 24 pulse rectifier, the proposed strategy can adjust the charging and discharging threshold of ESSs dynamically, which can not noly prevent the influence caused by fluctuation of no-load voltage, but also coordinate the energy flow of ESSs applied in multiple substations, and improve the overall performance of ESSs in energy saving and voltage stability. Then the paper verifies the effectiveness of proposed strategy under various running conditions of trains through simulation.In order to analyze the influence and improvement of super capacitor ESSs on DC network of urban rail power supply system qualitatively and quantitatively under different energy management strategy and configuration, this paper bases on the structure and principle of urban rail power supply system, establishes models of modules in the power supply system, and develops simulation platform of urban rail power supply system which contains intercoupling vehicles, substations and ESSs.This paper proposes a novel optimization method which combines hybrid particle swarm algorithm and simulation platform of urban rail power supply system, and elaborate the calculations method of objective function and enhancement principle of hybrid particle swarm algorithm in detail.The proposed intelligent optimization method can obtain the best control parameters of energy management strategy and configuration for ESSs simultaneously according to different urban railway line and optimization objective function. Finally, the optimization results are analyzed and summarized.This paper establishs an experiment platform for urban rail transit power supply system with two super capacitor ESSs, which can simulate the energy flow between different substations, vehicles and ESSs.Then the paper verifies the effectiveness of proposed strategy under different no-load voltages of substations and different running conditions of vehicles through experiment.